139 results on '"Taherian Fard A"'
Search Results
2. Ataxia Telangiectasia patient-derived neuronal and brain organoid models reveal mitochondrial dysfunction and oxidative stress
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Hannah C. Leeson, Julio Aguado, Cecilia Gómez-Inclán, Harman Kaur Chaggar, Atefah Taherian Fard, Zoe Hunter, Martin F. Lavin, Alan Mackay-Sim, and Ernst J. Wolvetang
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Ataxia telangiectasia ,Brain organoids ,Mitochondria ,Neurodegeneration ,Cellular senescence ,Oxidative stress ,Neurosciences. Biological psychiatry. Neuropsychiatry ,RC321-571 - Abstract
Ataxia Telangiectasia (AT) is a rare disorder caused by mutations in the ATM gene and results in progressive neurodegeneration for reasons that remain poorly understood. In addition to its central role in nuclear DNA repair, ATM operates outside the nucleus to regulate metabolism, redox homeostasis and mitochondrial function. However, a systematic investigation into how and when loss of ATM affects these parameters in relevant human neuronal models of AT was lacking. We therefore used cortical neurons and brain organoids from AT-patient iPSC and gene corrected isogenic controls to reveal levels of mitochondrial dysfunction, oxidative stress, and senescence that vary with developmental maturity. Transcriptome analyses identified disruptions in regulatory networks related to mitochondrial function and maintenance, including alterations in the PARP/SIRT signalling axis and dysregulation of key mitophagy and mitochondrial fission-fusion processes. We further show that antioxidants reduce ROS and restore neurite branching in AT neuronal cultures, and ameliorate impaired neuronal activity in AT brain organoids. We conclude that progressive mitochondrial dysfunction and aberrant ROS production are important contributors to neurodegeneration in AT and are strongly linked to ATM's role in mitochondrial homeostasis regulation.
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- 2024
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3. Senolytic therapy alleviates physiological human brain aging and COVID-19 neuropathology
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Aguado, Julio, Amarilla, Alberto A., Taherian Fard, Atefeh, Albornoz, Eduardo A., Tyshkovskiy, Alexander, Schwabenland, Marius, Chaggar, Harman K., Modhiran, Naphak, Gómez-Inclán, Cecilia, Javed, Ibrahim, Baradar, Alireza A., Liang, Benjamin, Peng, Lianli, Dharmaratne, Malindrie, Pietrogrande, Giovanni, Padmanabhan, Pranesh, Freney, Morgan E., Parry, Rhys, Sng, Julian D. J., Isaacs, Ariel, Khromykh, Alexander A., Valenzuela Nieto, Guillermo, Rojas-Fernandez, Alejandro, Davis, Thomas P., Prinz, Marco, Bengsch, Bertram, Gladyshev, Vadim N., Woodruff, Trent M., Mar, Jessica C., Watterson, Daniel, and Wolvetang, Ernst J.
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- 2023
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4. Measuring cell-to-cell expression variability in single-cell RNA-sequencing data: a comparative analysis and applications to B cell aging
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Huiwen Zheng, Jan Vijg, Atefeh Taherian Fard, and Jessica Cara Mar
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Cell-to-cell variability ,B lymphocytes differentiation ,Aging ,Single-cell RNA-seq ,Evaluation framework ,Biology (General) ,QH301-705.5 ,Genetics ,QH426-470 - Abstract
Abstract Background Single-cell RNA-sequencing (scRNA-seq) technologies enable the capture of gene expression heterogeneity and consequently facilitate the study of cell-to-cell variability at the cell type level. Although different methods have been proposed to quantify cell-to-cell variability, it is unclear what the optimal statistical approach is, especially in light of challenging data structures that are unique to scRNA-seq data like zero inflation. Results We systematically evaluate the performance of 14 different variability metrics that are commonly applied to transcriptomic data for measuring cell-to-cell variability. Leveraging simulations and real datasets, we benchmark the metric performance based on data-specific features, sparsity and sequencing platform, biological properties, and the ability to recapitulate true levels of biological variability based on known gene sets. Next, we use scran, the metric with the strongest all-round performance, to investigate changes in cell-to-cell variability that occur during B cell differentiation and the aging processes. The analysis of primary cell types from hematopoietic stem cells (HSCs) and B lymphopoiesis reveals unique gene signatures with consistent patterns of variable and stable expression profiles during B cell differentiation which highlights the significance of these methods. Identifying differentially variable genes between young and old cells elucidates the regulatory changes that may be overlooked by solely focusing on mean expression changes and we investigate this in the context of regulatory networks. Conclusions We highlight the importance of capturing cell-to-cell gene expression variability in a complex biological process like differentiation and aging and emphasize the value of these findings at the level of individual cell types.
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- 2023
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5. A Software Defined Networking Architecture for DDoS-Attack in the Storage of Multimicrogrids.
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Elahe Taherian Fard, Taher Niknam, Ramin Sahebi, Mahshid Javidsharifi, Abdollah Kavousi-Fard, and Jamshid Aghaei
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- 2022
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6. A Software Defined Networking Architecture for DDoS-Attack in the Storage of Multimicrogrids
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Elaheh Taherian-Fard, Taher Niknam, Ramin Sahebi, Mahshid Javidsharifi, Abdollah Kavousi-Fard, and Jamshid Aghaei
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Multi-microgrid ,software defined networking ,cloud-fog computing ,distributed denial of service attack (DDoS) ,optimization algorithm ,Electrical engineering. Electronics. Nuclear engineering ,TK1-9971 - Abstract
Multi-microgrid systems can improve the resiliency and reliability of the power system network. Secure communication for multi-microgrid operation is a crucial issue that needs to be investigated. This paper proposes a multi-controller software defined networking (SDN) architecture based on fog servers in multi-microgrids to improve the electricity grid security, monitoring and controlling. The proposed architecture defines the support vector machine (SVM) to detect the distributed denial of service (DDoS) attack in the storage of microgrids. The information of local SDN controllers on fog servers is managed and supervised by the master controller placed in the application plane properly. Based on the results of attack detection, the power scheduling problem is solved and send a command to change the status of tie and sectionalize switches. The optimization application on the cloud server implements the modified imperialist competitive algorithm (MICA) to solve this stochastic mixed-integer nonlinear problem. The effective performance of the proposed approach using an SDN-based architecture is evaluated through applying it on a multi-microgrid based on IEEE 33-bus radial distribution system with three microgrids in simulation results.
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- 2022
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7. Genetic and functional interaction network analysis reveals global enrichment of regulatory T cell genes influencing basal cell carcinoma susceptibility
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Christelle Adolphe, Angli Xue, Atefeh Taherian Fard, Laura A. Genovesi, Jian Yang, and Brandon J. Wainwright
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BCC ,GWAS ,Cancer susceptibility ,Immune surveillance ,Protein interaction networks ,Medicine ,Genetics ,QH426-470 - Abstract
Abstract Background Basal cell carcinoma (BCC) of the skin is the most common form of human cancer, with more than 90% of tumours presenting with clear genetic activation of the Hedgehog pathway. However, polygenic risk factors affecting mechanisms such as DNA repair and cell cycle checkpoints or which modulate the tumour microenvironment or host immune system play significant roles in determining whether genetic mutations culminate in BCC development. We set out to define background genetic factors that play a role in influencing BCC susceptibility via promoting or suppressing the effects of oncogenic drivers of BCC. Methods We performed genome-wide association studies (GWAS) on 17,416 cases and 375,455 controls. We subsequently performed statistical analysis by integrating data from population-based genetic studies of multi-omics data, including blood- and skin-specific expression quantitative trait loci and methylation quantitative trait loci, thereby defining a list of functionally relevant candidate BCC susceptibility genes from our GWAS loci. We also constructed a local GWAS functional interaction network (consisting of GWAS nearest genes) and another functional interaction network, consisting specifically of candidate BCC susceptibility genes. Results A total of 71 GWAS loci and 46 functional candidate BCC susceptibility genes were identified. Increased risk of BCC was associated with the decreased expression of 26 susceptibility genes and increased expression of 20 susceptibility genes. Pathway analysis of the functional candidate gene regulatory network revealed strong enrichment for cell cycle, cell death, and immune regulation processes, with a global enrichment of genes and proteins linked to TReg cell biology. Conclusions Our genome-wide association analyses and functional interaction network analysis reveal an enrichment of risk variants that function in an immunosuppressive regulatory network, likely hindering cancer immune surveillance and effective antitumour immunity.
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- 2021
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8. How does the structure of data impact cell-cell similarity? Evaluating how structural properties influence the performance of proximity metrics in single cell RNA-seq data.
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Ebony Rose Watson, Ariane Mora, Atefeh Taherian Fard, and Jessica Cara Mar
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- 2022
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9. Ataxia Telangiectasia patient-derived neuronal and brain organoid models reveal mitochondrial dysfunction and oxidative stress
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Leeson, Hannah C, primary, Aguado, Julio, additional, Gómez-Inclán, Cecilia, additional, Chaggar, Harman Kaur, additional, Taherian Fard, Atefah, additional, Hunter, Zoe, additional, Lavin, Martin F, additional, Mackay-Sim, Alan, additional, and Wolvetang, Ernst J, additional
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- 2024
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10. Therapy-induced lipid uptake and remodeling underpin ferroptosis hypersensitivity in prostate cancer
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Kaylyn D. Tousignant, Anja Rockstroh, Berwyck L. J. Poad, Ali Talebi, Reuben S. E. Young, Atefeh Taherian Fard, Rajesh Gupta, Tuo Zang, Chenwei Wang, Melanie L. Lehman, Johan V. Swinnen, Stephen J. Blanksby, Colleen C. Nelson, and Martin C. Sadowski
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Therapy resistance ,Multidrug tolerance ,Metabolic reprograming ,Lipid remodeling ,Lipid uptake ,Ferroptosis ,Neoplasms. Tumors. Oncology. Including cancer and carcinogens ,RC254-282 - Abstract
Abstract Background Metabolic reprograming, non-mutational epigenetic changes, increased cell plasticity, and multidrug tolerance are early hallmarks of therapy resistance in cancer. In this temporary, therapy-tolerant state, cancer cells are highly sensitive to ferroptosis, a form of regulated cell death that is caused by oxidative stress through excess levels of iron-dependent peroxidation of polyunsaturated fatty acids (PUFA). However, mechanisms underpinning therapy-induced ferroptosis hypersensitivity remain to be elucidated. Methods We used quantitative single-cell imaging of fluorescent metabolic probes, transcriptomics, proteomics, and lipidomics to perform a longitudinal analysis of the adaptive response to androgen receptor-targeted therapies (androgen deprivation and enzalutamide) in prostate cancer (PCa). Results We discovered that cessation of cell proliferation and a robust reduction in bioenergetic processes were associated with multidrug tolerance and a strong accumulation of lipids. The gain in lipid biomass was fueled by enhanced lipid uptake through cargo non-selective (macropinocytosis, tunneling nanotubes) and cargo-selective mechanisms (lipid transporters), whereas de novo lipid synthesis was strongly reduced. Enzalutamide induced extensive lipid remodeling of all major phospholipid classes at the expense of storage lipids, leading to increased desaturation and acyl chain length of membrane lipids. The rise in membrane PUFA levels enhanced membrane fluidity and lipid peroxidation, causing hypersensitivity to glutathione peroxidase (GPX4) inhibition and ferroptosis. Combination treatments against AR and fatty acid desaturation, lipase activities, or growth medium supplementation with antioxidants or PUFAs altered GPX4 dependence. Conclusions Our work provides mechanistic insight into processes of lipid metabolism that underpin the acquisition of therapy-induced GPX4 dependence and ferroptosis hypersensitivity to standard of care therapies in PCa. It demonstrates novel strategies to suppress the therapy-tolerant state that may have potential to delay and combat resistance to androgen receptor-targeted therapies, a currently unmet clinical challenge of advanced PCa. Since enhanced GPX4 dependence is an adaptive phenotype shared by several types of cancer in response to different therapies, our work might have universal implications for our understanding of metabolic events that underpin resistance to cancer therapies.
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- 2020
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11. Computational Methods for Single-Cell Imaging and Omics Data Integration
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Ebony Rose Watson, Atefeh Taherian Fard, and Jessica Cara Mar
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single cell imaging ,single cell omics ,data integration ,machine learning ,ageing ,Biology (General) ,QH301-705.5 - Abstract
Integrating single cell omics and single cell imaging allows for a more effective characterisation of the underlying mechanisms that drive a phenotype at the tissue level, creating a comprehensive profile at the cellular level. Although the use of imaging data is well established in biomedical research, its primary application has been to observe phenotypes at the tissue or organ level, often using medical imaging techniques such as MRI, CT, and PET. These imaging technologies complement omics-based data in biomedical research because they are helpful for identifying associations between genotype and phenotype, along with functional changes occurring at the tissue level. Single cell imaging can act as an intermediary between these levels. Meanwhile new technologies continue to arrive that can be used to interrogate the genome of single cells and its related omics datasets. As these two areas, single cell imaging and single cell omics, each advance independently with the development of novel techniques, the opportunity to integrate these data types becomes more and more attractive. This review outlines some of the technologies and methods currently available for generating, processing, and analysing single-cell omics- and imaging data, and how they could be integrated to further our understanding of complex biological phenomena like ageing. We include an emphasis on machine learning algorithms because of their ability to identify complex patterns in large multidimensional data.
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- 2022
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12. A Wavelet-Based Droop Control of Reactive Power Sharing and Frequency Regulation in Islanded Microgrids
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Sahebi, Ramin, primary, Mardaneh, Mohammad, additional, Jamshidpour, Ehsan, additional, Aghaei, Jamshid, additional, Taherian-Fard, Elaheh, additional, and Niknam, Taher, additional
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- 2023
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13. Deconstructing heterogeneity of replicative senescence in human mesenchymal stem cells at single cell resolution
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Taherian Fard, Atefeh, primary, Leeson, Hannah C., additional, Aguado, Julio, additional, Pietrogrande, Giovanni, additional, Power, Dominique, additional, Gómez-Inclán, Cecilia, additional, Zheng, Huiwen, additional, Nelson, Christopher B., additional, Soheilmoghaddam, Farhad, additional, Glass, Nick, additional, Dharmaratne, Malindrie, additional, Watson, Ebony R., additional, Lu, Jennifer, additional, Martin, Sally, additional, Pickett, Hilda A., additional, Cooper-White, Justin, additional, Wolvetang, Ernst J., additional, and Mar, Jessica C., additional
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- 2023
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14. Therapy-induced lipid uptake and remodeling underpin ferroptosis hypersensitivity in prostate cancer
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Tousignant, Kaylyn D., Rockstroh, Anja, Poad, Berwyck L. J., Talebi, Ali, Young, Reuben S. E., Taherian Fard, Atefeh, Gupta, Rajesh, Zang, Tuo, Wang, Chenwei, Lehman, Melanie L., Swinnen, Johan V., Blanksby, Stephen J., Nelson, Colleen C., and Sadowski, Martin C.
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- 2020
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15. Quantitative Modelling of the Waddington Epigenetic Landscape
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Taherian Fard, Atefeh, primary and Ragan, Mark A., additional
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- 2019
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16. Supplementary Data from Lipid Uptake Is an Androgen-Enhanced Lipid Supply Pathway Associated with Prostate Cancer Disease Progression and Bone Metastasis
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Tousignant, Kaylyn D., primary, Rockstroh, Anja, primary, Taherian Fard, Atefeh, primary, Lehman, Melanie L., primary, Wang, Chenwei, primary, McPherson, Stephen J., primary, Philp, Lisa K., primary, Bartonicek, Nenad, primary, Dinger, Marcel E., primary, Nelson, Colleen C., primary, and Sadowski, Martin C., primary
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- 2023
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17. Data from Lipid Uptake Is an Androgen-Enhanced Lipid Supply Pathway Associated with Prostate Cancer Disease Progression and Bone Metastasis
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Tousignant, Kaylyn D., primary, Rockstroh, Anja, primary, Taherian Fard, Atefeh, primary, Lehman, Melanie L., primary, Wang, Chenwei, primary, McPherson, Stephen J., primary, Philp, Lisa K., primary, Bartonicek, Nenad, primary, Dinger, Marcel E., primary, Nelson, Colleen C., primary, and Sadowski, Martin C., primary
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- 2023
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18. Supplemental Files from Lipid Uptake Is an Androgen-Enhanced Lipid Supply Pathway Associated with Prostate Cancer Disease Progression and Bone Metastasis
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Tousignant, Kaylyn D., primary, Rockstroh, Anja, primary, Taherian Fard, Atefeh, primary, Lehman, Melanie L., primary, Wang, Chenwei, primary, McPherson, Stephen J., primary, Philp, Lisa K., primary, Bartonicek, Nenad, primary, Dinger, Marcel E., primary, Nelson, Colleen C., primary, and Sadowski, Martin C., primary
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- 2023
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19. Closing the loop: Redesigning sustainable reverse logistics network in uncertain supply chains.
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Shahrooz Shahparvari, Hamed Soleimani, Kannan Govindan 0002, Behrooz Bodaghi, Mahshid Taherian Fard, and Hamid Jafari
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- 2021
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20. Supplemental Files from Lipid Uptake Is an Androgen-Enhanced Lipid Supply Pathway Associated with Prostate Cancer Disease Progression and Bone Metastasis
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Martin C. Sadowski, Colleen C. Nelson, Marcel E. Dinger, Nenad Bartonicek, Lisa K. Philp, Stephen J. McPherson, Chenwei Wang, Melanie L. Lehman, Atefeh Taherian Fard, Anja Rockstroh, and Kaylyn D. Tousignant
- Abstract
Figure S1: LNCaP, VCaP and DuCaP cells were grown in charcoal-dextran stripped serum (CSS) for 48 h and treated with increasing concentrations of R1881 or DHT in the presence or absence of Enzalutamide (10 µM) or vehicle (Ctrl) for 48 h. Figure S2: Androgens increased lipid uptake of long-chain fatty acids. LAPC4 cells were grown in CSS for 48 h and treated with 1 nM R1881 or vehicle for 48 h. Figure S3: (A) LNCaP cells were synchronized in G0/G1 by androgen deprivation (CSS for 48 h) followed by treatment with Tunicamycin (1 mg/mL), Hydroxyurea (1 M), or Nocodazole (25 ug/mL) for another 24 h, placing cell cycle blocks in G0/G1, S phase and mitosis, respectively. Figure S4: Oncomine analysis of candidate lipid transporters in (A) Grasso [2], (B) Varambally [3] and (C) LaTulippe datasets [4] comparing gene expression of normal prostate gland versus localized, primary prostate cancer tumor samples. Figure S5: (A) DuCaP (top panel) and VCaP cells (bottom panel) were grown in CSS for 48 h and treated with 10 nM DHT in the absence or presence of Enz (10 µM) or vehicle (Ctrl) for 48 h. Table S1. Primer sequences
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- 2023
21. Optimal distribution reconfiguration considering high penetration of electric vehicles.
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Amir Ghaedi, Elaheh Taherian Fard, Hadi Fotoohabadi, and Farzaneh Kavousi-Fard
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- 2016
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22. Senolytic therapy alleviates physiological human brain aging and COVID-19 neuropathology
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Aguado, Julio, primary, Amarilla, Alberto A., additional, Taherian Fard, Atefeh, additional, Albornoz, Eduardo A., additional, Tyshkovskiy, Alexander, additional, Schwabenland, Marius, additional, Chaggar, Harman K., additional, Modhiran, Naphak, additional, Gómez-Inclán, Cecilia, additional, Javed, Ibrahim, additional, Baradar, Alireza A., additional, Liang, Benjamin, additional, Dharmaratne, Malindrie, additional, Pietrogrande, Giovanni, additional, Padmanabhan, Pranesh, additional, Freney, Morgan E., additional, Parry, Rhys, additional, Sng, Julian D.J., additional, Isaacs, Ariel, additional, Khromykh, Alexander A., additional, Rojas-Fernandez, Alejandro, additional, Davis, Thomas P., additional, Prinz, Marco, additional, Bengsch, Bertram, additional, Gladyshev, Vadim N., additional, Woodruff, Trent M., additional, Mar, Jessica C., additional, Watterson, Daniel, additional, and Wolvetang, Ernst J., additional
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- 2023
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23. scShapes: a statistical framework for identifying distribution shapes in single-cell RNA-sequencing data
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Dharmaratne, Malindrie, primary, Kulkarni, Ameya S, additional, Taherian Fard, Atefeh, additional, and Mar, Jessica C, additional
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- 2022
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24. Senolytic therapy alleviates physiological human brain aging and COVID-19 neuropathology
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Julio Aguado, Alberto Amarilla, Atefeh Taherian Fard, Eduardo Albornoz, Alexander Tyshkovskiy, Marius Schwabenland, Harman Chaggar, Naphak Modhiran, Cecilia Gómez-Inclán, Ibrahim Javed, Alireza Baradar, Benjamin Liang, Malindrie Dharmaratne, Giovanni Pietrogrande, Pranesh Padmanabhan, Morgan Freney, Rhys Parry, Julian Sng, Ariel Isaacs, Alexander Khromykh, Alejandro Rojas-Fernandez, Thomas Davis, Marco Prinz, Bertram Bengsch, Vadim Gladyshev, Trent Woodruff, Jessica Mar, Daniel Watterson, and Ernst Wolvetang
- Abstract
Aging is the primary risk factor for most neurodegenerative diseases, and recently coronavirus disease 2019 (COVID-19) has been associated with severe neurological manifestations that can eventually impact neurodegenerative conditions in the long-term. The progressive accumulation of senescent cellsin vivostrongly contributes to brain aging and neurodegenerative co-morbidities but the impact of virus-induced senescence in the aetiology of neuropathologies is unknown. Here, we show that senescent cells accumulate in physiologically aged brain organoids of human origin and that senolytic treatment reduces inflammation and cellular senescence; for which we found that combined treatment with the senolytic drugs dasatinib and quercetin rejuvenates transcriptomic human brain aging clocks. We further interrogated brain frontal cortex regions in postmortem patients who succumbed to severe COVID-19 and observed increased accumulation of senescent cells as compared to age-matched control brains from non-COVID-affected individuals. Moreover, we show that exposure of human brain organoids to SARS-CoV-2 evoked cellular senescence, and that spatial transcriptomic sequencing of virus-induced senescent cells identified a unique SARS-CoV-2 variant-specific inflammatory signature that is different from endogenous naturally-emerging senescent cells. Importantly, following SARS-CoV-2 infection of human brain organoids, treatment with senolytics blocked viral retention and prevented the emergence of senescent corticothalamic and GABAergic neurons. Furthermore, we demonstrate in human ACE2 overexpressing mice that senolytic treatment ameliorates COVID-19 brain pathology following infection with SARS-CoV-2.In vivotreatment with senolytics improved SARS-CoV-2 clinical phenotype and survival, alleviated brain senescence and reactive astrogliosis, promoted survival of dopaminergic neurons, and reduced viral and senescence-associated secretory phenotype gene expression in the brain. Collectively, our findings demonstrate SARS-CoV-2 can trigger cellular senescence in the brain, and that senolytic therapy mitigates senescence-driven brain aging and multiple neuropathological sequelae caused by neurotropic viruses, including SARS-CoV-2.
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- 2023
25. scShapes: a statistical framework for identifying distribution shapes in single-cell RNA-sequencing data
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Malindrie Dharmaratne, Atefeh Taherian Fard, Ameya Kulkarni, and Jessica Mar
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Health Informatics ,Computer Science Applications - Abstract
Background Single-cell RNA sequencing (scRNA-seq) methods have been advantageous for quantifying cell-to-cell variation by profiling the transcriptomes of individual cells. For scRNA-seq data, variability in gene expression reflects the degree of variation in gene expression from one cell to another. Analyses that focus on cell–cell variability therefore are useful for going beyond changes based on average expression and, instead, identifying genes with homogeneous expression versus those that vary widely from cell to cell. Results We present a novel statistical framework, scShapes, for identifying differential distributions in single-cell RNA-sequencing data using generalized linear models. Most approaches for differential gene expression detect shifts in the mean value. However, as single-cell data are driven by overdispersion and dropouts, moving beyond means and using distributions that can handle excess zeros is critical. scShapes quantifies gene-specific cell-to-cell variability by testing for differences in the expression distribution while flexibly adjusting for covariates if required. We demonstrate that scShapes identifies subtle variations that are independent of altered mean expression and detects biologically relevant genes that were not discovered through standard approaches. Conclusions This analysis also draws attention to genes that switch distribution shapes from a unimodal distribution to a zero-inflated distribution and raises open questions about the plausible biological mechanisms that may give rise to this, such as transcriptional bursting. Overall, the results from scShapes help to expand our understanding of the role that gene expression plays in the transcriptional regulation of a specific perturbation or cellular phenotype. Our framework scShapes is incorporated into a Bioconductor R package (https://www.bioconductor.org/packages/release/bioc/html/scShapes.html).
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- 2022
26. Measuring cell-to-cell expression variability in single-cell RNA-sequencing data: a comparative analysis and applications to B cell ageing
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Huiwen Zheng, Jan Vijg, Atefeh Taherian Fard, and Jessica Cara Mar
- Abstract
BackgroundSingle-cell RNA-sequencing (scRNA-seq) technologies enable the capture of gene expression heterogeneity and consequently cell-to-cell variability at the cell type level. Although different methods have been proposed to quantify cell-to-cell variability, it is unclear what the optimal statistical approach is, especially in light of challenging data structures that are unique to scRNA-seq data like zero inflation.ResultsIn this study, we conducted a systematic evaluation of cell-to-cell gene expression variability using 14 different variability metrics that are commonly applied to transcriptomic data. Performance was evaluated with respect to data-specific features like sparsity and sequencing platform, biological properties like gene length, and the ability to recapitulate true levels of variability based on simulation and known biological gene sets like ribosomal genes and stably expressed genes. scran had the strongest all-round performance, and this metric was then applied to investigate the changes in cell-to-cell variability that occur during ageing. Studying ageing showcases the value of cell-to-cell variability as it is a genetically-regulated program that is influenced by stochastic processes.scRNA-seq datasets from hematopoietic stem cells (HSCs) and B lymphocytes and other cell types from this differentiation lineage were used with scran to identify the genes with consistent patterns of variable and stable expression profiles during differentiation. Furthermore, to understand the regulatory relationship for genes that were differentially-variable in their expression between young and old mice, we constructed networks using transcription factors and their known targets for HSC and B lymphocyte cells. Comparisons of these networks identified a shared TFSfpi1that although was seen to increase in gene expression variability in old mice versus young in both cell types, the corresponding targets were distinct and their gene expression variability had different directions between cell types.ConclusionsThrough these analyses, we highlight the importance of capturing cell-to-cell gene expression variability in a complex biological process like differentiation and ageing, and emphasise the value and specificity of interpreting these findings at the level of individual cell types.
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- 2022
27. Breast cancer classification: linking molecular mechanisms to disease prognosis.
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Atefeh Taherian Fard, Sriganesh Srihari, and Mark A. Ragan
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- 2015
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28. Redox signaling regulates breast cancer metastasis via HIF1α-stimulated EMT dynamics and metabolic reprogramming
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Zuen Ren, Malindrie Dharmaratne, Huizhi Liang, Outhiriaradjou Benard, Miriam Morales-Gallego, Kimita Suyama, Atefeh Taherian Fard, Jessica C. Mar, Michael Prystowsky, Larry Norton, and Rachel B. Hazan
- Abstract
Metastasis is orchestrated by phenotypic and metabolic reprogramming underlying tumor aggressiveness. Redox signaling by mammary tumor knockdown (KD) of the antioxidant glutathione peroxidase 2 (GPx2) enhanced metastasis via dynamic changes in epithelial-to-mesenchymal transition. Single cell RNA sequencing (scRNA-seq) of the control and PyMT/GPx2 KD mammary tumor revealed six luminal and one basal/mesenchymal like (cluster 3) subpopulations. Remarkably, GPx2 KD enhanced the size and basal/mesenchymal gene signature of cluster 3 as well as induced epithelial/mesenchymal (E/M) clusters which expressed markers of oxidative phosphorylation and glycolysis, indicative of hybrid metabolism. These data were validated in human breast cancer xenografts and were supported by pseudotime cell trajectory analysis. Moreover, the E/M and M states were both attenuated by GPx2 gain of function or HIF1α inhibition, leading to metastasis suppression. Collectively, these results demonstrate that redox/HIF1α signaling promotes mesenchymal gene expression, resulting in E/M clusters and a mesenchymal root subpopulation, driving phenotypic and metabolic heterogeneity underlying metastasis.SignificanceBy leveraging single cell RNA analysis, we were able to demonstrate that redox signaling by GPx2 loss in mammary tumors results in HIF1α signaling, which promotes partial and full EMT conversions, represented by distinct tumor cell subpopulations, which in turn express hybrid and binary metabolic states. These data underscore a phenotypic and metabolic co-adaptation in cancer, arguing in favor of the GPx2-HIF1α axis as a therapeutic platform for targeting tumor cell metastasis.
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- 2022
29. How does the structure of data impact cell–cell similarity? Evaluating how structural properties influence the performance of proximity metrics in single cell RNA-seq data
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Watson, Ebony Rose, primary, Mora, Ariane, additional, Taherian Fard, Atefeh, additional, and Mar, Jessica Cara, additional
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- 2022
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30. Effect of Extremely Low Frequency Electromagnetic Field and/or GABAB Receptors on Foot Shock-induced Aggression in Rats
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Mahnaz Taherian Fard, Aminollah Bahaeddini, Tahoora Shomali, and Saeideh Karimi Haghighi
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Aggressive behavior ,Extremely low frequency electromagnetic field ,GABAB receptors ,Rats ,Neurosciences. Biological psychiatry. Neuropsychiatry ,RC321-571 - Abstract
Introduction: The present study investigated the interactive effect of GABAB receptors and extremely low frequency electromagnetic field (ELF-EMF) on foot shock-induced aggression in rats. Methods: fifty adult male rats were randomly assigned into 10 groups. Groups 2, 4, 6, 8 and 10 were exposed to 50 Hz, 500 µT ELF-EMF for 30 days 8h per day while the remaining groups (1, 3, 5, 7 and 9) were sham-exposed. At the end of this period, the animals in groups 1 and 2 received normal saline while groups 3 and 4 treated with 100 mg/kg (low dose) of CGP35348 and groups 5 and 6 injected with 200 mg/kg (high dose) of CGP35348. Groups 7 and 8 treated with 1.7 mg/kg (low dose) of Baclofen and groups 9 and 10 received 3 mg/kg (high dose) Baclofen by IP injections. Twenty min after the injection, the aggressive behavior was recorded in foot shock-induced aggression model. The number of lateral threat, lifted up threat, biting, attacking, chasing and approaching were considered as paradigms of aggressive behavior. Results: ELF-EMF, Baclofen or CGP35348 alone had no significant effect on aggressive behavior. Except that rats exposed and treated with low dose of CGP35348 demonstrated significantly higher numbers of only one of the paradigms of aggressive behavior (lifted up threats), CGP35348 and Baclofen in both doses in combination with ELF-EMF exposure had no significant effect on aggression. Discussion: GABAB receptors and ELF-EMFs had no effect (both enhancement and suppression) on aggressive behavior of rats in foot shock-induced model of aggression.
- Published
- 2014
31. How does data structure impact cell-cell similarity? Evaluating the influence of structural properties on proximity metric performance in single cell RNA-seq data
- Author
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Ebony Rose Watson, Ariane Mora, Atefeh Taherian Fard, and Jessica Cara Mar
- Abstract
Accurately identifying cell populations is paramount to the quality of downstream analyses and overall interpretations of single-cell RNA-seq (scRNA-seq) datasets but remains a challenge. The quality of single-cell clustering depends on the proximity metric used to generate cell-to-cell distances. Accordingly, proximity metrics have been benchmarked for scRNA-seq clustering, typically with results averaged across datasets to identify a highest performing metric. However, the ‘best-performing’ metric varies between studies, with the performance differing significantly between datasets. This suggests that the unique structural properties of a scRNA-seq dataset, specific to the biological system under study, has a substantial impact on proximity metric performance. Previous benchmarking studies have omitted to factor the structural properties into their evaluations. To address this gap, we developed a framework for the in-depth evaluation of the performance of 17 proximity metrics with respect to core structural properties of scRNA-seq data, including sparsity, dimensionality, cell population distribution and rarity. We find that clustering performance can be improved substantially by the selection of an appropriate proximity metric and neighbourhood size for the structural properties of a dataset, in addition to performing suitable pre-processing and dimensionality reduction. Furthermore, popular metrics such as Euclidean and Manhattan distance performed poorly in comparison to several lessor applied metrics, suggesting the default metric for many scRNA-seq methods should be re-evaluated. Our findings highlight the critical nature of tailoring scRNA-seq analyses pipelines to the system under study and provide practical guidance for researchers looking to optimise cell similarity search for the structural properties of their own data.
- Published
- 2022
32. Discovering Molecular Regulators of Ageing Using Mixture Models With RNA-sequencing Data
- Author
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Sasdekumar Loganathan, Ameya Kulkarni, Atefeh Taherian Fard, and Jessica Mar
- Abstract
Identifying the molecular regulators that control ageing is challenging because the ageing process is influenced by a combination of genetic and environmental factors which makes it difficult to source the contribution of a single gene. Multiple studies have demonstrated that as humans age, increased gene expression heterogeneity results in the dysregulation of key regulators and pathways. Given the dynamic nature of gene expression, it is vital that this data be modelled by statistical approaches that can appropriately account for changes in variability to understand the contribution of heterogeneity during the aging process and properly identify its regulators. This study demonstrates the utility of using mixture models to model biological variability of gene expression occurring during ageing and how novel potential regulators of ageing can be identified.Our mixture modelling approach was applied to gene expression data from the Genotype-Tissue Expression (GTEx) cohort. For every gene, the expression profile was modelled using a mixture model across the cohort where the subset of donors corresponding to each mode was tested for a significant change in age group. The multi-tissue aspect of GTEx was leveraged to find ageing regulators based on this mixture model approach genes that were common across multiple tissues, suggesting that the regulation of ageing may also be controlled through a set of genes that have non-tissue-specific activity. Our approach identified the common ageing regulator mTOR, as significantly associated with a mixture model profile but this gene was not detected through standard differential expression analysis using edgeR. Genes identified by the standard approaches like edgeR and the mixture model-based approach were found to be enriched for similar biological pathways. This suggests that while the specific ageing regulators identified from our approach may be distinct, they generally belong in the same pathways as the genes that are identified by standard approaches. Overall, these results indicate that modelling gene expression variability using mixture models in conjunction with standard differential gene expression can help uncover new regulators that have a potential role for understanding human ageing.
- Published
- 2022
33. An efficient hybrid algorithm based on modified imperialist competitive algorithm and K-means for data clustering.
- Author
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Taher Niknam, Elahe Taherian Fard, Narges Pourjafarian, and Alireza Rousta
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- 2011
- Full Text
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34. Therapy-induced lipid uptake and remodeling underpin ferroptosis hypersensitivity in prostate cancer
- Author
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Berwyck L. J. Poad, Ali Talebi, Melanie Lehman, Kaylyn D. Tousignant, Johan Swinnen, Tuo Zang, Martin C. Sadowski, Rajesh Gupta, Chenwei Wang, Colleen C. Nelson, Stephen J. Blanksby, Atefeh Taherian Fard, Reuben S. E. Young, and Anja Rockstroh
- Subjects
CASTRATION ,CELL-SURVIVAL ,Multidrug tolerance ,Membrane lipids ,STEROIDOGENESIS ,PROGRESSION ,GPX4 ,lcsh:RC254-282 ,DESATURATION ,Lipid peroxidation ,chemistry.chemical_compound ,Lipidomics ,Lipid remodeling ,Membrane fluidity ,Enzalutamide ,Ferroptosis ,ANDROGEN-DEPRIVATION ,Science & Technology ,Prostate cancer ,RECEPTOR ,MOLECULAR-MECHANISMS ,Research ,Therapy resistance ,Metabolic reprograming ,Lipid metabolism ,Lipid uptake ,Cell Biology ,CHOLESTEROL TRAFFICKING ,lcsh:Neoplasms. Tumors. Oncology. Including cancer and carcinogens ,Psychiatry and Mental health ,Oncology ,chemistry ,Cancer cell ,Cancer research ,Life Sciences & Biomedicine ,RESISTANCE - Abstract
BackgroundMetabolic reprograming, non-mutational epigenetic changes, increased cell plasticity and multidrug tolerance are early hallmarks of therapy resistance in cancer. In this temporary, therapy-tolerant state, cancer cells are highly sensitive to ferroptosis, a form of regulated cell death that is caused by oxidative stress through excess levels of iron-dependent peroxidation of polyunsaturated fatty acids (PUFA). However, mechanisms underpinning therapy-induced ferroptosis hypersensitivity remain to be elucidated.MethodsWe used quantitative single cell imaging of fluorescent metabolic probes, transcriptomics, proteomics and lipidomics to perform a longitudinal analysis of the adaptive response to androgen receptor-targeted therapies (androgen deprivation and enzalutamide) in prostate cancer (PCa).ResultsWe discovered that cessation of cell proliferation and a robust reduction in bioenergetic processes were associated with multidrug tolerance and a strong accumulation of lipids. The gain in lipid biomass was fueled by enhanced lipid uptake through cargo non-selective (macropinocytosis, tunneling nanotubes) and cargo-selective mechanisms (lipid transporters), whereasde novolipid synthesis was strongly reduced. Enzalutamide induced extensive lipid remodeling of all major phospholipid classes at the expense of storage lipids, leading to increased desaturation and acyl chain length of membrane lipids. The rise in membrane PUFA levels enhanced membrane fluidity and lipid peroxidation, causing hypersensitivity to glutathione peroxidase (GPX4) inhibition and ferroptosis. Combination treatments against AR and fatty acid desaturation, lipase activities or growth medium supplementation with antioxidants or PUFAs altered GPX4 dependence. Despite multidrug tolerance, PCa cells displayed an enhanced sensitivity to inhibition of lysosomal processing of exogenous lipids, highlighting an increased dependence on lipid uptake in the therapy-tolerant state.ConclusionsOur work provides mechanistic insight into processes of lipid metabolism that underpin the acquisition of therapy-induced GPX4 dependence and ferroptosis hypersensitivity to standard of care therapies in PCa. It demonstrated novel strategies to suppress the therapy-tolerant state that may have potential to delay and combat resistance to androgen receptor-targeted therapies, a currently unmet clinical challenge of advanced PCa. Since enhanced GPX4 dependence is an adaptive phenotype shared by several types of cancer in response to different therapies, our work might have universal implications for our understanding of metabolic events that underpin resistance to cancer therapies.
- Published
- 2020
35. DoS-Resilient Distributed Optimal Scheduling in a Fog Supporting IIoT-Based Smart Microgrid
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Afshin Izadian, Abdollah Kavousi-Fard, Mohammad Mardaneh, Elaheh Taherian-Fard, Seyede Zahra Tajalli, Taher Niknam, and Morteza Dabbaghjamanesh
- Subjects
business.industry ,Energy management ,Computer science ,020209 energy ,Distributed computing ,020208 electrical & electronic engineering ,Cloud computing ,Denial-of-service attack ,02 engineering and technology ,Industrial and Manufacturing Engineering ,Electricity generation ,Control and Systems Engineering ,Computer data storage ,0202 electrical engineering, electronic engineering, information engineering ,Microgrid ,Electrical and Electronic Engineering ,business ,Dispatchable generation ,Wireless sensor network - Abstract
Industrial Internet of Things (IIoT) is an architecture that facilitates the feasibility of the distributed control of the modernized industrial systems mainly through the Internet of Things and cloud computing. This article proposes an optimal scheduling framework for the real-time operation of smart microgrids in the IIoT environment using an average consensus-based algorithm. The introduced framework suggests a fog layer as a complementary layer of IIoT to reduce latency and provide local computation and data storage for the proposed industry. Security of the system against probable attacks is the other concern that should be observed. To this end, this article sets out to evaluate the impact of a particular type of attack called the denial of service on the performance of the proposed method. Accuracy, feasibility, and fast response of the scheme are demonstrated through simulation results on a microgrid test system in the presence of dispatchable and nondispatchable generation units with heterogeneous devices.
- Published
- 2020
36. Wind Turbine Drivetrain Technologies
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Afshin Izadian, Mokhtar Shasadeghi, Elaheh Taherian-Fard, Taher Niknam, and Ramin Sahebi
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Wind power ,Emerging technologies ,Computer science ,business.industry ,020208 electrical & electronic engineering ,Drivetrain ,02 engineering and technology ,01 natural sciences ,Turbine ,Industrial and Manufacturing Engineering ,Automotive engineering ,Electricity generation ,Fluid power ,Reliability (semiconductor) ,Control and Systems Engineering ,0103 physical sciences ,0202 electrical engineering, electronic engineering, information engineering ,Electric power ,Electrical and Electronic Engineering ,010306 general physics ,business - Abstract
Employment of a specific technology in the conversion of wind energy to electrical power highly influences the cost and reliability of power generation. To help the selection of the best drivetrain technology, this article presents a thorough review of three major wind turbine drivetrains, namely gearbox, direct drive, and hydrostatic. Although the gearbox drivetrain has offered a mature and applicable technology, some inherent difficulties and manufacturing of specific generators and advancements in fluid power machinery resulted in new technologies that are true competitors of the gearbox. The cost, performance, and functionality of these drivetrains are now comparable with the gearbox peers. This article presents a comprehensive review of three different types of the drivetrain and their generators. This article particularly helps researchers and the engineers in the field with new insight into all technologies.
- Published
- 2020
37. Deconstructing replicative senescence heterogeneity of human mesenchymal stem cells at single cell resolution reveals therapeutically targetable senescent cell sub-populations
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Atefeh Taherian Fard, Hannah Leeson, Julio Aguado Perez, Giovanni Pietrogrande, Dominique Power, Cecilia Liliana Gomez Inclan, Huiwen Zheng, Christopher Nelson, Farhad Soheilmoghaddam, Nick Glass, Malindrie Dharmaratne, Ebony R. Watson, Jennifer Lu, Sally Martin, Hilda Pickett, Justin Cooper-White, Ernst Wolvetang, and Jessica C. Mar
- Abstract
Cellular senescence is characterised by a state of permanent cell cycle arrest. It is accompanied by often variable release of the so-called senescence-associated secretory phenotype (SASP) factors, and occurs in response to a variety of triggers such as persistent DNA damage, telomere dysfunction, or oncogene activation. While cellular senescence is a recognised driver of organismal ageing, the extent of heterogeneity within and between different senescent cell populations remains largely unclear. Elucidating the drivers and extent of variability in cellular senescence states is important for discovering novel targeted seno-therapeutics and for overcoming cell expansion constraints in the cell therapy industry. Here we combine cell biological and single cell RNA-sequencing approaches to investigate heterogeneity of replicative senescence in human ESC-derived mesenchymal stem cells (esMSCs) as MSCs are the cell type of choice for the majority of current stem cell therapies and senescence of MSC is a recognized driver of organismal ageing. Our data identify three senescent subpopulations in the senescing esMSC population that differ in SASP, oncogene expression, and escape from senescence. Uncovering and defining this heterogeneity of senescence states in cultured human esMSCs allowed us to identify potential drug targets that may delay the emergence of senescent MSCsin vitroand perhapsin vivoin the future.
- Published
- 2022
38. Bayesian Non-Parametric Mixture Models Reveal Modes of Regulation in Chromatin Accessibility and Identifies Genes That Define Cell Identity
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Malindrie Dharmaratne, Atefeh Taherian Fard, and Jessica Mar
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History ,Polymers and Plastics ,Business and International Management ,Industrial and Manufacturing Engineering - Published
- 2022
39. A Software Defined Networking Architecture for DDoS-Attack in the storage of Multi-Microgrids
- Author
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Elaheh Taherian-Fard, Taher Niknam, Ramin Sahebi, Mahshid Javidsharifi, Abdollah Kavousi-Fard, and Jamshid Aghaei
- Subjects
Optimization ,Denial-of-service attack ,distributed denial of service attack (DDoS) ,Support vector machines ,General Computer Science ,General Engineering ,Multi-microgrid ,optimization algorithm ,Servers ,Edge computing ,Reliability ,Software defined networking ,cloud-fog computing ,Cloud computing ,General Materials Science ,Computer architecture ,Electrical and Electronic Engineering ,Microgrids - Abstract
Multi-microgrid systems can improve the resiliency and reliability of the power system network. Secure communication for multi-microgrid operation is a crucial issue that needs to be investigated. This paper proposes a multi-controller software defined networking (SDN) architecture based on fog servers in multi-microgrids to improve the electricity grid security, monitoring and controlling. The proposed architecture defines the support vector machine (SVM) to detect the distributed denial of service (DDoS) attack in the storage of microgrids. The information of local SDN controllers on fog servers is managed and supervised by the master controller placed in the application plane properly. Based on the results of attack detection, the power scheduling problem is solved and send a command to change the status of tie and sectionalize switches. The optimization application on the cloud server implements the modified imperialist competitive algorithm (MICA) to solve this stochastic mixed-integer nonlinear problem. The effective performance of the proposed approach using an SDN-based architecture is evaluated through applying it on a multi-microgrid based on IEEE 33-bus radial distribution system with three microgrids in simulation results.
- Published
- 2022
40. Redox signaling by glutathione peroxidase 2 links vascular modulation to metabolic plasticity of breast cancer
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Zuen Ren, Huizhi Liang, Phillip M. Galbo, Malindrie Dharmaratne, Ameya S. Kulkarni, Atefeh Taherian Fard, Marie Louise Aoun, Nuria Martinez-Lopez, Kimita Suyama, Outhiriaradjou Benard, Wei Zheng, Yang Liu, Joseph Albanese, Deyou Zheng, Jessica C. Mar, Rajat Singh, Michael B. Prystowsky, Larry Norton, and Rachel B. Hazan
- Subjects
Vascular Endothelial Growth Factor A ,Glutathione Peroxidase ,Multidisciplinary ,Neovascularization, Pathologic ,Cell Plasticity ,Mice, Nude ,Breast Neoplasms ,Hypoxia-Inducible Factor 1, alpha Subunit ,Xenograft Model Antitumor Assays ,Oxidative Phosphorylation ,Mice ,Metabolism ,Cell Line, Tumor ,Animals ,Humans ,Female ,Reactive Oxygen Species ,Glycolysis ,Oxidation-Reduction ,Signal Transduction - Abstract
In search of redox mechanisms in breast cancer, we uncovered a striking role for glutathione peroxidase 2 (GPx2) in oncogenic signaling and patient survival. GPx2 loss stimulates malignant progression due to reactive oxygen species/hypoxia inducible factor-α (HIF1α)/VEGFA (vascular endothelial growth factor A) signaling, causing poor perfusion and hypoxia, which were reversed by GPx2 reexpression or HIF1α inhibition. Ingenuity Pathway Analysis revealed a link between GPx2 loss, tumor angiogenesis, metabolic modulation, and HIF1α signaling. Single-cell RNA analysis and bioenergetic profiling revealed that GPx2 loss stimulated the Warburg effect in most tumor cell subpopulations, except for one cluster, which was capable of oxidative phosphorylation and glycolysis, as confirmed by coexpression of phosphorylated-AMPK and GLUT1. These findings underscore a unique role for redox signaling by GPx2 dysregulation in breast cancer, underlying tumor heterogeneity, leading to metabolic plasticity and malignant progression.
- Published
- 2021
41. Computational Methods for Single-Cell Imaging and Omics Data Integration
- Author
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Watson, Ebony Rose, primary, Taherian Fard, Atefeh, additional, and Mar, Jessica Cara, additional
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- 2022
- Full Text
- View/download PDF
42. Bayesian Non-Parametric Mixture Models Reveal Modes of Regulation in Chromatin Accessibility and Identifies Genes That Define Cell Identity
- Author
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Dharmaratne, Malindrie, primary, Taherian Fard, Atefeh, additional, and Mar, Jessica, additional
- Published
- 2022
- Full Text
- View/download PDF
43. A Software Defined Networking Architecture for DDoS-Attack in the Storage of Multimicrogrids
- Author
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Taherian-Fard, Elaheh, primary, Niknam, Taher, additional, Sahebi, Ramin, additional, Javidsharifi, Mahshid, additional, Kavousi-Fard, Abdollah, additional, and Aghaei, Jamshid, additional
- Published
- 2022
- Full Text
- View/download PDF
44. scShapes: a statistical framework for identifying distribution shapes in single-cell RNA-sequencing data.
- Author
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Dharmaratne, Malindrie, Kulkarni, Ameya S, Taherian Fard, Atefeh, and Mar, Jessica C
- Subjects
GENE expression ,RNA sequencing ,PHENOTYPES ,GENETIC transcription regulation ,OPEN-ended questions - Abstract
Background Single-cell RNA sequencing (scRNA-seq) methods have been advantageous for quantifying cell-to-cell variation by profiling the transcriptomes of individual cells. For scRNA-seq data, variability in gene expression reflects the degree of variation in gene expression from one cell to another. Analyses that focus on cell–cell variability therefore are useful for going beyond changes based on average expression and, instead, identifying genes with homogeneous expression versus those that vary widely from cell to cell. Results We present a novel statistical framework, scShapes , for identifying differential distributions in single-cell RNA-sequencing data using generalized linear models. Most approaches for differential gene expression detect shifts in the mean value. However, as single-cell data are driven by overdispersion and dropouts, moving beyond means and using distributions that can handle excess zeros is critical. scShapes quantifies gene-specific cell-to-cell variability by testing for differences in the expression distribution while flexibly adjusting for covariates if required. We demonstrate that scShapes identifies subtle variations that are independent of altered mean expression and detects biologically relevant genes that were not discovered through standard approaches. Conclusions This analysis also draws attention to genes that switch distribution shapes from a unimodal distribution to a zero-inflated distribution and raises open questions about the plausible biological mechanisms that may give rise to this, such as transcriptional bursting. Overall, the results from scShapes help to expand our understanding of the role that gene expression plays in the transcriptional regulation of a specific perturbation or cellular phenotype. Our framework scShapes is incorporated into a Bioconductor R package (https://www.bioconductor.org/packages/release/bioc/html/scShapes.html). [ABSTRACT FROM AUTHOR]
- Published
- 2023
- Full Text
- View/download PDF
45. Closing the loop:Redesigning sustainable reverse logistics network in uncertain supply chains
- Author
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Kannan Govindan, Mahshid Taherian Fard, Shahrooz Shahparvari, Hamed Soleimani, Hamid Jafari, and Behrooz Bodaghi
- Subjects
Mathematical optimization ,021103 operations research ,Carbon tax ,General Computer Science ,Stochastic modelling ,Heuristic (computer science) ,Computer science ,Heuristic ,Supply chain ,Sustainable reverse logistics ,0211 other engineering and technologies ,General Engineering ,Uncertainty ,02 engineering and technology ,Reverse logistics ,Stochastic programming ,Taguchi methods ,Closed-loop supply chain ,0202 electrical engineering, electronic engineering, information engineering ,Return rate ,020201 artificial intelligence & image processing ,Stochastic optimization ,Carbon emission policy ,Robust stochastic optimization ,Carbon credit - Abstract
This paper develops a robust stochastic optimization model for reverse logistics in closed-loop supply chains. By determining the optimal flow of products using a Chance Constrained Robust Stochastic Programming (CCRSP), it is highlighted how the number of plant openings is influenced by the changes in carbon credit price. To assess the model performance, a set of numerical experiments in different sizes are developed and conducted. The effectiveness of the results are then compared to a proposed Heuristic Hybrid Taguchi PSO (HTPSO) solution algorithm, which underlines the effectiveness of the model. A sensitivity analysis on the carbon emission rate is carried out which underlines the role of Carbon Tax Policy. Finally, a real-life case study within the automotive manufacturing industry is carried out by applying the developed robust stochastic model. From a practical standpoint, the model can potentially be employed to meet the carbon credits that are used for handling the different carbon prices and trade scenarios. Also, it provides insights on how to better manage uncertainties, as well as to reduce the overall emissions in supply chains.
- Published
- 2021
46. 3D asymmetric carbozole hole transporting materials for perovskite solar cells
- Author
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Nima Taghavinia, Fariba Tajabadi, Esmaeil Sheibani, Mahsa Heydari, Hosein Ahangar, Hajar Mohammadi, Hossein Taherian Fard, and Mahmoud Samadpour
- Subjects
Electron mobility ,Materials science ,Renewable Energy, Sustainability and the Environment ,business.industry ,Carbazole ,020209 energy ,Energy conversion efficiency ,02 engineering and technology ,021001 nanoscience & nanotechnology ,law.invention ,chemistry.chemical_compound ,chemistry ,law ,0202 electrical engineering, electronic engineering, information engineering ,Moiety ,Optoelectronics ,General Materials Science ,Grain boundary ,Crystallization ,0210 nano-technology ,business ,Glass transition - Abstract
Carbazole compounds are p-type hole-transporting materials (HTMs) useful for perovskite solar cells (PSCs). In this work, we developed a new class of carbazol based HTMs; non-fused 3-D asymmetric structures (S14 and S12) as HTM of PSCs. To the best of our knowledge, there is no report on non-fused HTMs with a high glass transition temperature (Tg = 165 °C), which reduces crystallization and suppresses grain boundaries in glassy film, resulting in long-term durability. Experimental results show that tuning the carbazole moiety in S14 structure has a constructive influence on geometrical alignment, hole mobility, hydrophobicity, stability as well as efficiency. The resultant power conversion efficiency (PCE) of devices were 15.31% and 11.85% for S14 and S12, respectively. Cell efficiency decreases during the first day for all devices. But after this time, the cell efficiency of the device fabricated with S14 remains constant until 1000 h at atmospheric condition without encapsulation while for devices fabricated by S12 and Spiro-OMeTAD the cell efficiency decreases to 75% and 69%.
- Published
- 2019
47. Lipid Uptake Is an Androgen-Enhanced Lipid Supply Pathway Associated with Prostate Cancer Disease Progression and Bone Metastasis
- Author
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Stephen McPherson, Marcel E. Dinger, Chenwei Wang, Martin C. Sadowski, Kaylyn D. Tousignant, Anja Rockstroh, Atefeh Taherian Fard, Lisa Philp, Nenad Bartonicek, Colleen C. Nelson, and Melanie Lehman
- Subjects
Male ,0301 basic medicine ,Cancer Research ,medicine.medical_treatment ,Bone Neoplasms ,Metastasis ,03 medical and health sciences ,Prostate cancer ,chemistry.chemical_compound ,0302 clinical medicine ,Cell Line, Tumor ,medicine ,Humans ,Enzalutamide ,Gene Regulatory Networks ,Molecular Biology ,Fatty Acids ,Prostatic Neoplasms ,Bone metastasis ,Lipid Metabolism ,medicine.disease ,Gene Expression Regulation, Neoplastic ,Lipoproteins, LDL ,Androgen receptor ,Steroid hormone ,Cholesterol ,030104 developmental biology ,Microscopy, Fluorescence ,Oncology ,chemistry ,Receptors, Androgen ,030220 oncology & carcinogenesis ,Lipogenesis ,Cancer cell ,Androgens ,Disease Progression ,Cancer research ,Signal Transduction - Abstract
De novo lipogenesis is a well-described androgen receptor (AR)–regulated metabolic pathway that supports prostate cancer tumor growth by providing fuel, membrane material, and steroid hormone precursor. In contrast, our current understanding of lipid supply from uptake of exogenous lipids and its regulation by AR is limited, and exogenous lipids may play a much more significant role in prostate cancer and disease progression than previously thought. By applying advanced automated quantitative fluorescence microscopy, we provide the most comprehensive functional analysis of lipid uptake in cancer cells to date and demonstrate that treatment of AR-positive prostate cancer cell lines with androgens results in significantly increased cellular uptake of fatty acids, cholesterol, and low-density lipoprotein particles. Consistent with a direct, regulatory role of AR in this process, androgen-enhanced lipid uptake can be blocked by the AR-antagonist enzalutamide, but is independent of proliferation and cell-cycle progression. This work for the first time comprehensively delineates the lipid transporter landscape in prostate cancer cell lines and patient samples by analysis of transcriptomics and proteomics data, including the plasma membrane proteome. We show that androgen exposure or deprivation regulates the expression of multiple lipid transporters in prostate cancer cell lines and tumor xenografts and that mRNA and protein expression of lipid transporters is enhanced in bone metastatic disease when compared with primary, localized prostate cancer. Our findings provide a strong rationale to investigate lipid uptake as a therapeutic cotarget in the fight against advanced prostate cancer in combination with inhibitors of lipogenesis to delay disease progression and metastasis. Implications: Prostate cancer exhibits metabolic plasticity in acquiring lipids from uptake and lipogenesis at different disease stages, indicating potential therapeutic benefit by cotargeting lipid supply.
- Published
- 2019
48. Abstract 968: Loss of glutathione peroxidase 2 promotes epithelial to mesenchymal transition and breast cancer metastasis
- Author
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Zuen Ren, Huizhi Liang, Malindrie Dharmaratne, Miriam Morales-Gallego, Atefeh Taherian Fard, Jessica Mar, Kimita Suyama, Outhiriaradjou Benard, Michael B. Prystowsky, Larry Norton, and Rachel B. Hazan
- Subjects
Cancer Research ,Oncology - Abstract
The processes regulating tumor metastasis are multivariate and complex. Redox regulation of the tumor phenotype by GPx2 knockdown (KD) in breast cancer led us to uncover dramatic effects on spontaneous metastasis. Analysis of single cell RNA sequencing (scRNAseq) data from GPx2 KD tumor and control tumor, revealed that both tumors were comprised of several luminal-like tumor cell clusters and one mesenchymal-like cell cluster (cluster 3). Notably, GPx2 KD promoted a significant increase in the size of mesenchymal cells (cluster 3) relative to control, which might be due to the stimulation of epithelial-to-mesenchymal transition (EMT) in response to GPx2 loss. In support of this view, GPx2 KD stimulated an increase in mRNA expression of basal/mesenchymal (KRT5, KRT14, KRT17, Vimentin, Twist1, Twist2, CDH2) genes and a decrease in mRNA expression of epithelial/luminal (Cldn7 and Epcam) genes, especially in cluster 3. Moreover, GPx2 KD upregulated mRNA expression of basal/mesenchymal (Twist2, CDH2, and KRT14) genes in most luminal-like clusters expressing epithelial/luminal (Epcam, Cldn3/7, CDH1, KRT8/18) genes, implying these clusters may be undergoing EMT transition in a hybrid epithelial/mesenchymal state in response to GPx2 loss. Validation of these data in cell lines and tumors showed that GPx2 KD dramatically enhanced EMT via activation of ROS/HIF1α-mediated signaling. Importantly, these effects were reversed by GPx2 re-expression or HIF1α inhibition, which was capable of suppressing EMT and metastasis. Collectively, these results indicate that GPx2 loss promotes breast cancer metastasis by stimulating EMT due to HIF1α signaling, highlighting the impact of GPx2 and HIF1 on therapeutic intervention in metastasis. Citation Format: Zuen Ren, Huizhi Liang, Malindrie Dharmaratne, Miriam Morales-Gallego, Atefeh Taherian Fard, Jessica Mar, Kimita Suyama, Outhiriaradjou Benard, Michael B. Prystowsky, Larry Norton, Rachel B. Hazan. Loss of glutathione peroxidase 2 promotes epithelial to mesenchymal transition and breast cancer metastasis [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2022; 2022 Apr 8-13. Philadelphia (PA): AACR; Cancer Res 2022;82(12_Suppl):Abstract nr 968.
- Published
- 2022
49. Breast cancer classification: linking molecular mechanisms to disease prognosis
- Author
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Taherian-Fard, Atefeh, Srihari, Sriganesh, and Ragan, Mark A.
- Published
- 2015
- Full Text
- View/download PDF
50. Dynamics and Control of a Shared Wind Turbine Drivetrain
- Author
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Afshin Izadian, Taher Niknam, Mohsen Farbood, Elaheh Taherian-Fard, and Mokhtar Shasadeghi
- Subjects
0209 industrial biotechnology ,Wind power ,Electrical load ,business.industry ,Computer science ,Drivetrain ,02 engineering and technology ,Turbine ,Industrial and Manufacturing Engineering ,Maximum power point tracking ,020901 industrial engineering & automation ,Electricity generation ,Control and Systems Engineering ,Control theory ,Control system ,0202 electrical engineering, electronic engineering, information engineering ,Torque ,020201 artificial intelligence & image processing ,Electrical and Electronic Engineering ,business - Abstract
This paper presents the dynamics and control of a new wind power plant configuration where multiple turbines are connected to a shared drivetrain. A hydrostatic transmission system is utilized to collect and transfer the harvested mechanical energy of individual turbines to the generator. The interconnected wind turbines are controlled individually to achieve maximum power point tracking (MPPT) while regulating the generator speed. In the first control loop, the pump displacement is adjusted accordingly to satisfy the MPPT. In the second control loop, the electrical load on the generator is controlled to balance the torque and reach a stable frequency operation. Simulation results show the performance of the control system operation. It also demonstrates an increase and improved smoothness of a power generation profile.
- Published
- 2018
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